Degradation and breakdown behaviors of SGTs under repetitive unclamped inductive switching avalanche stress

The repetitive unclamped inductive switching(UIS)avalanche stress is conducted to investigate the degradation and breakdown behaviors of conventional shield gate trench MOSFET(C-SGT)and P-ring SGT MOSFETs(P-SGT).It is found that the static and dynamic parameters of both devices show different degrees of degradation.Combining experimental and simulation results,the hot holes trapped into the Si/SiO_(2) interface and the increase of crystal lattice temperature should be responsible for the degradation and breakdown behaviors.Moreover,under repetitive UIS avalanche stress,the reliability of P-SGT overcomes that of C-SGT,benefitting from the decreasing of the impact ionization rate at bottom of field oxide caused by the existence of P-ring.

Separation of cortical arteries and veins in optical neurovascular imaging

Separation of arteries and veins in the cerebral cortex is of significant importance in the studies of cortical hemodynamics,such as the changes of cerebral blood flow,perfusion or oxygen con-centration in arteries and veins under different pathological and physiological conditions.Yet the cerebral vessel segmentation and vessel-type separation are challenging due to the complexity of cortical vessel characteristics and low spatial signal-to-noise ratio.In this work,we presented an effective full-field method to differentiate arteries and veins in cerebral cortex using dual-modal optical imaging technology including laser speckle imaging(LSI)and optical intrinsic signals(OIS)imaging.The raw contrast images were acquired by LSI and processed with enhanced laser speckle contrast analysis(eLASCA),algorithm.The vascular pattern was extracted and seg-mented using region growing algorithm from the eLASCA-based LSI.Meanwhile,OIS imageswere acquired altermatively with 630 and 870 nm to obtain an oxy hemoglobin concentration mapover cerebral cortex.Then the separation of arteries and veins was accomplished by Otsuthreshold segmentation algorithm based on the OIS information and segmentation of LSI.Finally,the segmentation and separation performances were assessed using area overlap measure(AOM).The segmentation and separation of cerebral vessels in cortical optical imaging have great potential applications in full-field cerebral hemodynamics monitoring and pathological study of cerebral vascular diseases,as well as in clinical intraoperative monitoring.

Precipitation data and their uncertainty as input for rainfallinduced shallow landslide models

Physical models used toforecast the temporal occurrence of rainfall-induced shallow landslides are based on deterministic laws.Owing to the existing measuring technology and our knowledge of the physical laws controlling landslide initiation,model uncertainties are due to an inability to accurately quantify the model input parameters and rainfall forcing data.An uncertainty analysis of slope instability prediction provides a rationale for refining the geotechnical models.The Transient Rainfall Infiltration and Grid-based Regional Slope Stability-Probabilistic(TRIGRS-P)model adopts a probabilistic approach to compute the changes in the Factor of Safety(FS)due to rainfall infiltration.Slope Infiltration Distributed Equilibrium(SLIDE)is a simplified physical model for landslide prediction.The new code(SLIDE-P)is also modified by adopting the same probabilistic approach to allow values of the SLIDE model input parameters to be sampled randomly.This study examines the relative importance of rainfall variability and the uncertainty in the other variables that determine slope stability.The precipitation data from weather stations,China Meteorological Administration Land Assimilation System 2.0(CLDAS2.0),China Meteorological Forcing Data set precipitation(CMFD),and China geological hazard bulletin are used to drive TRIGRS,SLIDE,TRIGRS-P and SLIDE-P models.The TRIGRS-P and SLIDE-P models are used to generate the input samples and to calculate the values of FS.The outputs of several model runs with varied input parameters and rainfall forcings are analyzed statistically.A comparison suggests that there are significant differences in the simulations of the TRIGRS-P and SLIDE-P models.Although different precipitation data sets are used,the simulation results of TRIGRS-P are more concentrated.This study can inform the potential use of numerical models toforecast the spatial and temporal occurrence of regional rainfall-induced shallow landslides.

BMA probability quantitative precipitation forecasting of land-falling typhoons in south-east China

The probability of quantitative precipitation forecast(PQPF)of three Bayesian Model Averaging(BMA)models based on three raw super ensemble prediction schemes(i.e.,A,B,and C)are established,which through calibration of their parameters using 1-3 day precipitation ensemble prediction systems(EPSs)from the China Meteorological Administration(CMA),the European Centre for Medium-Range Weather Forecasts(ECMWF)and the National Centers for Environmental Prediction(NCEP)and observation during land-falling of three typhoons in south-east China in 2013.The comparison of PQPF shows that the performance is better in the BMA than that in raw ensemble forecasts.On average,the mean absolute error(MAE)of 1 day lead time forecast is reduced by 12.4%,and its continuous ranked probability score(CRPS)of 1-3 day lead time forecast is reduced by 26.2%,respectively.Although the amount of precipitation prediction by the BMA tends to be underestimated,but in view of the perspective of probability prediction,the probability of covering the observed precipitation by the effective forecast ranges of the BMA are increased,which is of great significance for the early warning of torrential rain and secondary disasters induced by it.